An information criterion for model selection with missing data via complete-data divergence

We derive an information criterion to select a parametric model of complete-data distribution when only incomplete or partially observed data are available. Compared with AIC, our new criterion has an additional penalty term for missing data, which is expressed by the Fisher information matrices of complete data and incomplete data. We prove that our criterion is an asymptotically unbiased estimator of complete-data divergence, namely the expected Kullback–Leibler divergence between the true distribution and the estimated distribution for complete data, whereas AIC is that for the incomplete data. The additional penalty term of our criterion for missing data turns out to be only half the value of that in previously proposed information criteria PDIO and AICcd. The difference in the penalty term is attributed to the fact that our criterion is derived under a weaker assumption. A simulation study with the weaker assumption shows that our criterion is unbiased while the other two criteria are biased. In addition, we review the geometrical view of alternating minimizations of the EM algorithm. This geometrical view plays an important role in deriving our new criterion.     

A general criterion for optimal structural design

A general criterion of structural optimality is presented and discussed. It applies to multipurpose structures subjected to multiple or movable loadings, the design of which is defined by several design functions. The cost is assumed to be a convex function of the various specific energies associated with the respective behavioral constraints. This criterion is shown to include most (if not all) criteria used up to now.     

A penalized criterion for variable selection in classification

In this paper, the problem of variable selection in classification is considered. On the basis of recent developments in model selection theory, we provide a criterion based on penalized empirical risk, where the penalization explicitly takes into account the number of variables of the considered models. Moreover, we give an oracle-type inequality that non-asymptotically guarantees the performance of the resulting classification rule. We discuss the optimality of the proposed criterion and present an application of the main result to backward and forward selection procedures.     

Some general divergence measures for probability distributions

Summary General divergence measures for probability distributions are introduced and their main properties established. Connections with f-divergence corresponding to a convex function fare explored.     

A strongly consistent information criterion for linear model selection based on M-estimation

In this paper, a linear model selection procedure based on M-estimation is proposed, which includes many classical model selection criteria as its special cases. It is shown that the proposed criterion is strongly consistent under certain mild conditions, for instance without assuming normality of the distribution of the random errors. The results from a simulation study are also presented. Received: 13 October 1997 / Revised version: 10 August 1998     

A criterion for unitary similarity of upper triangular matrices in general position

Each square complex matrix is unitarily similar to an upper triangular matrix with diagonal entries in any prescribed order. Let A=[a_ij] and B=[b_ij] be upper triangular n×n matrices that

•

are not similar to direct sums of square matrices of smaller sizes, or

•

are in general position and have the same main diagonal.

We prove that A and B are unitarily similar if and only if

     

A general criterion to determine the number of change-points

A general criterion is proposed to determine the number K of the change-points in a parametric nonlinear multi-response model. Schwarz criterion is a particular case. The change-points depend on regressor values and not on instant of measure. We prove that the proposed estimator for K is consistent. Simulation results, using Monte Carlo technique, for nonlinear models which have numerous applications, support the relevance of the theory.     

Elimination of divergence of various types — A general scheme

Sverdlovsk. Translated from Sibirskii Matematicheskii Zhurnal, Vo. 29, No. 6, pp. 66–73, November–December, 1988.     

A practical general approximation criterion for methods of multipliers based on Bregman distances

 This paper demonstrates that for generalized methods of multipliers for convex programming based on Bregman distance kernels – including the classical quadratic method of multipliers – the minimization of the augmented Lagrangian can be truncated using a simple, generally implementable stopping criterion based only on the norms of the primal iterate and the gradient (or a subgradient) of the augmented Lagrangian at that iterate. Previous results in this and related areas have required conditions that are much harder to verify, such as ε-optimality with respect to the augmented Lagrangian, or strong conditions on the convex program to be solved. Here, only existence of a KKT pair is required, and the convergence properties of the exact form of the method are preserved. The key new element in the analysis is the use of a full conjugate duality framework, as opposed to mainly examining the action of the method on the standard dual function of the convex program. An existence result for the iterates, stronger than those possible for the exact form of the algorithm, is also included. Received: February 6, 2001 / Accepted: January 25, 2003 Published online: March 21, 2003 Mathematics Subject Classification (1991): 90C25, 90C46, 47H05     

Linearity criterion for the selection of an optimal tree

The aim of this paper is to present a method for selecting the optimal tree among the possible trees that can be generated starting from the a data set. Analysis a quantity criterion is used through the linear combination of the quality measurements of the tree, namely, resubstitution error and linearity. The application of the method leads to a succession of optimal trees, in such a way, that an element of the succession is associated with each possible value of the linear combination's parameter α.     

A symmetry result for a general class of divergence form PDEs in fibered media

In R^m×R^n−m, endowed with coordinates X=(x,y), we consider the PDE

     

The Condorcet criterion and committee selection

Recent studies have evaluated election procedures on their propensity to select committees that meet a Condorcet criterion. The Condorcet criterion has been defined to use majority agreement from voters' preferences to compare the selected committee to all other committees. This study uses a different definition of the Condorcet criterion as defined on committees. The focus of the new definition is on candidates. That is, we consider majority agreement on each candidate in the selected committee as compared to each candidate not in the selected committee.This new definition of the Condorcet criterion allows for the existence of majority cycles on candidates within the selected committee. However, no candidate in the non-selected group is able to defeat any candidate in the selected committee by majority rule. Of particular interest is the likelihood that a committee meeting this Condorcet criterion exists. Attention is also given to the likelihood that various simple voting procedures will select a committee meeting this Condorcet criterion when one does exist.     

Singular perturbations as a selection criterion for periodic minimizing sequences

Summary Minimizers of functionals like subject to periodic (or Dirichlet) boundary conditions are investigated. While for =0 the infimum is not attained it is shown that for sufficiently small > 0, all minimizers are periodic with period ^1/3. Connections with solid-solid phase transformations are indicated.     

A two-sided Arnoldi algorithm with stopping criterion and MIMO selection procedure

In this paper we introduce a two-sided Arnoldi method for the reduction of high order linear systems and we propose useful extensions, first of all a stopping criterion to find a suitable order for the reduced model and secondly, a selection procedure to significantly improve the performance in the multi-input multi-output (MIMO) case. One application is in micro-electro-mechanical systems (MEMS). We consider a thermo-electric micro thruster model, and a comparison between the commonly used Arnoldi algorithm and the two-sided Arnoldi is performed.     

A criterion for subnormality

Archiv der Mathematik -     

A criterion for unit-regularity

Summary A von Neumann regular ring is unit-regular if and only if every principal right ideal is uniquely generated.